Molecular distance-edge vector (mu) and chromatographic retention index ofalkanes

A new method of quantitative structure-retention relationship (QSRR) is pro posed for estimating and predicting gas chromatographic retention indices o f alkanes by using a novel molecular distance-edge vector, called mu vector , containing 10 elements. The QSRR model (M1), between the mu vector and ch romatographic retention indices of 64 alkanes, was developed by using multi ple linear regression (MLR) with the correlation coefficient being R = 0.99 92 and the root mean square (RMS) error between the estimated and measured retention indices being RMS = 5.938. In order to explain the equation stabi lity and prediction abilities of the M1 model, it is essential to perform a cross-validation (CV) procedure. Satisfactory CV results have been obtaine d by using one external predicted sample every time with the average correl ation coefficient being R = 0.9988 and average RMS = 7.128. If 21 compounds , about one third drawn from all 64 alkanes, construct an external predicti on set and the 43 remaining construct an internal calibration set, the seco nd QSRR model (M2) can be created by using calibration set data with statis tics being R = 0.9993 and RMS = 5.796. The chromatographic retention indice s of 21 compounds in the external testing set can be predicted by the M2 mo del and good prediction results are obtained with R = 0.9988 and RMS = 6.50 8.